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SPE 1610

PredictinShale ResJim Witkowsk

Copyright 2012, Society

This paper was prepare

This paper was selecteeviewed by the Societyfficers, or members. Eeproduce in print is res

Abstract Accurate quantThe literature dhe use of uran

response equatcalibration for possible some taking the medi

Many shalekerogen by volporosity shale r

Pyrite is comenhanced organ

Consequentconsider the prpyrite concentr

The link bepyrite and sulfusulfur for predimany other shndicator for in

ntroduction Organic-rich shHowever, the mwithin the orgaThermal maturi

The compleamounts of heasource rocks, sshould be takedecrease the reresistivity logs

Several loggamma-ray lineand the DeltaLog calibration

097

g Pyrite aservoir In

ky, James Gal

y of Petroleum Enginee

ed for presentation at t

d for presentation by ay of Petroleum EngineElectronic reproductionstricted to an abstract o

tification of totdescribes manynium content otion-based mevalidation. Eactechniques wilian average of e reservoirs colume. High voreservoirs, eachmmonly presennic matter prestly, in shale reresence of pyrations.

etween pyrite pur may be usefuicting TOC in

hale reservoirs.dividual wells,

hales are genematrix micro-panic matter devity is an imporex mineralogyavy minerals (such as the Haen into considesistivity respo(such as Delta-based methodear regression,ogR approach derived from p

and Totalnterpretatlford, John Qu

ers

he SPE Eastern Regio

an SPE program commeers and are subject ton, distribution, or storaof not more than 300 w

tal organic cary log-based apr GR linear re

ethod using soch of these tecl not produce rTOC estimates

ontain 10 wt% olumetric perceh 0.02 g/cm3 ernt in organic-rervation, and iservoirs, any m

rite. Similarly,

presence and thful TOC indica

shale reservoi. An interestin, the calibration

erally anisotropporosity residesvelops through rtant componeny of organic-ri(elements) conaynesville, is peration when

onse because iaLogR or a respds to predict T bulk density, (Passey et al.

pyrolysis measu

l Organiction uirein, Jerom

onal Meeting held in Le

mittee following review o correction by the autage of any part of thiswords; illustrations may

rbon (TOC) is proaches for p

egression, bulkonic, density, chniques involvreliable resultss from several pyrite and tot

entages of pyrirror in grain deich shale intervt may play a romethod of pred

TOC predicti

he depositionators in some siirs, such as in ng result is thn is not univers

pic and horizos in the intercrythe transforma

nt in determininich shales inc

ntained within pyrite, where 1interpreting re

it is highly conponse-equationOC have beenneural network1990). To be uurements perfo

c Carbon

e Truax, Halli

exington, Kentucky, US

of information containthor(s). The material ds paper without the wry not be copied. The ab

an important spredicting TOC

density, the Dand resistivit

ves assumption. However, gooindicators.

tal organic carite and kerogeensity producesvals of shale gole in decreasedicting TOC uions based on

al environmentituations. This the Haynesvill

hat, although isally applicabl

ontally laminatystalline poresation of kerogeng producibilit

cludes quartz, the matrix. Th

10 wt% pyrite esistivity logs.nductive. Con

n approach) shon developed anks, response equseful, all of thormed on core

from We

iburton

SA, 3–5 October 2012.

ned in an abstract submdoes not necessarily reritten consent of the Sbstract must contain co

step in evaluatC that have beeDeltaLogR appty logs. All ons for them to od log-based T

rbon (TOC), wen significantlys approximatel

gas formations ed resistivity reusing resistivity

bulk-density l

t for many orgpaper examinele shale reservit may be posle.

ted with a coms and in organien to hydrocarty and hydrocacalcite, feldsphe most comm(7 vol%) is su

. When presennsequently, anyould also consind reported in tquations involvhese methods samples.

ell Logs fo

.

mitted by the author(s)eflect any position of tSociety of Petroleum Eonspicuous acknowled

ting log data inen introduced

proach, neural of the approacbe valid, and,

TOC quantifica

which translatey affect the rocly 1 p.u. error ibecause of the

esponse if the vy logs, such aslogs may also

ganic-rich shalees the possiblevoir, but resultsssible to calibr

mplex pore geic matter. Abunrbons with incrarbon type. pars, pyrite, kmon heavy minufficient to affnt in appreciaby method of pider the presenthe literature tving sonic, denmust be valida

or Enhan

). Contents of the papehe Society of PetroleuEngineers is prohibitedgment of SPE copyrig

n organic-rich over the yearsnetwork approches require c, in a given insations can be a

es to 7% pyriteck grain densitin porosity. e reducing condvolume is suffics DeltaLogR, s

be sensitive t

e reservoirs su application ofs should be aprate a TOC-ba

eometry and mndant secondarreasing therma

kerogen, clays,neral in kerog

ffect grain denble amounts,

predicting TOCnce of pyrite. that use uraniunsity and resisated by way of

ncing

er have not been um Engineers, its ed. Permission to ght.

reservoirs. s, including oach, and a core-to-log stance, it is achieved by

e and 20% ty. In low-

ditions that cient. should also to elevated

uggests that f pyrite and pplicable to ased pyrite

mineralogy. ry porosity

al maturity.

, and trace gen-bearing sity, and it pyrite will

C that uses

um content, stivity logs, f a core-to-

2

itwwuoaocT HTbthcd

CmHfla

inadthWzs

2

Accurate evt is closely tie

will result in thworkflow for lusing several Tobtained by takassumptions thorganic-rich recounties. OtherThus, it is adva

Haynesville GThe Haynesvillbasin during thhe north-north

carbonate (limeduring plate sep

Fig. 1 showClay content gematter; the totaHaynesville shfrom bioturbataminated silice

The basin ncreased moly

are concentratedeposition (Hamhe reservoir ch

Where clastic dzones containinsecondary poro

valuation of TOd to kerogen c

he predicted polog analysis inTOC indicatorking a median

hat may not apeservoirs, suchr TOC indicatantageous to ha

Geology le shale is a h

he time of contiheast by deltaicestone and doloparation (Pope

ws an example enerally rangesal organic conteale is thermallted calcareouseous organic-riperiodically e

ybdenum conteed along and bemmes et al. 20haracterizationdilution has ocng abundant, thosity within the

OC is an imporcontent, which orosity being ton organic shalers (Quirein et n average of spply in a partich as the Hayneors are genera

ave a large num

ighly productiinental plate se

c deposits of saomites platformet al. 2009). Tternary diagrams from 40 to 50ent ranges fromly mature and mudstone, laich mudstone (exhibited restrent, the presencetween platform011). The depon. Matrix microccurred, interghermally matue organic matte

Fig. 1—

rtant part of logstrongly influ

oo high by an ae reservoirs inval. 2010). Ou

several TOC incular instance.esville shale, bally superior, bmber of potenti

ve gas shale theparation, withandstone and sm) and to the sThis encompassm of clay, quar0 wt%, but canm 2% to more highly overpr

aminated calca(Quirein et al. 2ricted environmce of framboidms and islands

ositional and dio-porosity resi

granular porosiure organic mater, as shown in

—Example Hayn

g analysis, giveences neutron,amount approxvolves derivin

ur experience ndicators. Eac This paper foby examining but additional al TOC indicat

hat was deposh its accompanshale, to the nosouth-southeastses the countiertz, and calciten be significantthan 5 wt% inessured. Haynareous mudsto2010). ment and red

dal pyrite, and s that providediagenetic historides in primaryity co-exists wtter, the transfoFig. 2.

nesville Shale M

en the complex, density, and sximately equal ng a continuouis that good l

ch of the TOCocuses on usincore data fromindicators maktors to choose

sited in quiet wnying rifting anorth-northwest,t by subaqueou

es in East Texae content from tly lower in th

n more anoxic pnesville mudrocone, and silty,

ducing anoxic TOC-S-Fe rela

d restrictive andry created a coy intercrystalli

within the primformation of ke

Mineralogy (wt%

xity of organic sonic logs. Noto the volume

us TOC estimalog-based TOC

C indicators mng pyrite and sm nine wells ke the medianfrom.

water within a nd basin subsid, west, and souus remnants ofs and northern one of the wele calcite-rich aportions of thecks contain a , peloidal sili

conditions, aationships. Thed anoxic condiomplex pore gine pores, as w

mary intercrystaerogen to dry g

%).

S

shale reservoiot accounting f

of kerogen. Aate from logginC quantificatio

mentioned abovsulfur to predispanning eigh

n prediction mo

restricted shaldence. It was reuthwest by shaf the continent

Louisiana. lls in the nine-wareas. It is riche basin (Spain 2variety of faciceous mudsto

as indicated bese organic-ricitions during Heometry that c

well as in orgaalline matrix pgas has created

SPE 161097

rs, because for kerogen

An effective ng data by ons can be ve involves ict TOC in ht different ore robust.

llow ocean estricted to

allow-water left behind

well study. h in organic 2010). The ies ranging ne, to un-

by variably ch intervals Haynesville complicates anic matter. porosity. In d abundant

S

nHsceo

SPE 161097

Fig. 2

For this papnine HaynesvilHarrison, Panostar symbols incomplete set oenergy dispersionly XRD and

Fig. 3—

2—Scanning Ele

per, we studiedlle wells locatla, and Rusk c

n Fig. 3, whichof core measurive X-ray fluorTOC measurem

—Haynesville Sh

ectron Microsco

d the results frted in Bienvillcounties of Eash also provide rements, inclurescence (ED-Xments were ava

hale Play Texas

ope Photograph

rom laboratoryle, Bossier, D

st Texas. Approan overview o

uding X-ray diXRF), and TOailable.

and Louisiana

h Showing Seco

y mineralogicalesota, and Reoximate locatio

of wells drillediffraction (XRD

OC, were carrie

Basin, Courtesy

ondary Porosity

l data and pyroed River parishons of the stud

d in the HaynesD), Inductiveled out for one

y of the U.S. En

y Formed within

olysis performhes of norther

dy wells are indsville-Bossier ly Couple Plasof the wells. F

nergy Informatio

Organic Matter

ed on core samrn Louisiana adicated by the shale as of Masma spectroscFor the other e

on Administratio

3

r.

mples from and Gregg, black-blue

ay 2011. A opy (ICP),

eight wells,

on.

4 SPE 161097

Core Measurements X-ray Diffraction. The mineralogy data used in this study came from X-ray diffraction measurements performed on core material. XRD is an analytical technique based on physical principles. It is one of the most commonly-used methods for quantitative mineral analysis of core material. A benchmark XRD study by Ruessink et al. (1992) on synthetic mineral mixtures showed that 90% of the XRD results fell within 5 wt% of the actual concentrations, and the results from reservoir core material were consistent with these findings. Moreover, they found that the accuracy of XRD results was comparable to the analysis of bulk mineralogy.

XRD is not a foolproof methodology; proper preparation and handling of sample materials are important for obtaining good results. For example, it is assumed that all minerals are randomly oriented; an overestimation of mineral phases can occur if samples are not prepared properly. In addition, selection of sample material is important to not bias the overall mineralogical variations in heterogeneous formations. An example of this would be selecting material for analysis where visually-obvious, large-pyrite nodules occur, while most of the pyrite is dispersed framboids. An advantage of XRD is that clay minerals are isolated and analyzed separately from the sand/silt fraction of the sample. Mica is a challenge for XRD; the best way to quantify micas is by thin-section petrography. XRD provides an accurate quantification of stoichiometric carbonate minerals, such as calcite, aragonite, and siderite (Ruessink, et al. 1992).

For this study, XRD was used to analyze Haynesville core samples for quartz, calcite, orthoclase feldspar, chlorite, plagioclase, illite/mixed layer clay, dolomite, and pyrite. Inductive Coupled Plasma Spectroscopy. Inductive Coupled Plasma (ICP) (Evans Analytical Group) spectroscopy uses a plasma source created when energy is supplied by an electric current that is produced by electromagnetic induction. ICP has become the industry standard for measuring 47 elements.

The ICP data used in this study were obtained from optical emission spectra (OES) for the oxides: SiO2, CaO, Fe2O3, Al2O3, K2O, P2O5, MgO, MnO, Na2O, P2O5, and TiO2. Energy Dispersive X-ray Fluorescence. Interaction of an electron beam with a sample target produces a variety of emissions, including X-rays. An energy-dispersive (ED) detector separates the characteristic X-rays from different elements into an energy spectrum that can be used to find the chemical composition of materials down to a spot size of a few microns. X-ray fluorescence (XRF) is a relatively non-destructive process to obtain chemical analyses of rocks, minerals, sediments, and fluids. It is typically used for bulk analysis of larger fractions of geological materials, making it one of the most widely-used methods for analysis of major and trace elements in rocks, minerals, and sediment.

ED-XRF measurements were used in this study to obtain the sulfur content of core samples. Total Organic Carbon Analysis. There are several methods and services available to measure TOC content and maturity of core samples, such as: Total Inorganic Carbon (TIC) and Total Carbon (TC) (LECO), Rock-Evaluation, Vitrinite Reflectance(VR), Kerogen Type, and Thermal Alteration Index.

All of the core TOC data used in this study were obtained with LECO TOC. Pyrite Mechanism Black shale is defined (McGraw-Hill) as fine-grained sedimentary rocks containing 3–15% organic carbon preserved as kerogen with clay-sized particles under anoxic and reducing conditions with abundant sulfides present. In basins where waters are calm (low-energy environments), the levels of oxygen remain stagnant near the surface where large amounts of organic matter, usually phytoplankton, collect. As organic matter accumulates and begins to settle, most of the organic material is oxidized to produce carbon dioxide. Eventually, the amount of organic material depletes the oxygen content, resulting in an anoxic environment (reducing conditions), as shown in Fig. 4. This reducing condition arises from a lack of oxygen from bacterial action, which cause organic shales to preserve large amounts of metals (pyrite) and rare-earth elements. Sulfates in the reaction are extracted from seawater, whereas methane is produced from bacteria. Pyrite appears as crystals distributed unevenly throughout the rock matrix. Although detrital and sedimentary pyrite occurs, most pyrite in sedimentary rocks is of diagenetic origin and does not result from a transportation/deposition process (Klimentos et al. 1995).

S

SFsplissthpinw

SPE 161097

Fig. 4—Pr

Sulfur-Iron-TFig. 5 shows crshows that uncpoints tend to bine (R2=0.56).

should follow tsulfur slope shohe sulfur data.

pyrite. This resn illite. Nor do

well. The cross

rocesses Affect

TOC Relationross-plots of suconstrained regbe more coline If all of the itrend lines pasould be 0.87. In This makes it

sult is not surproes it imply ths-plot in Fig. 6

ing Organic Ma

ships ulfur and iron gression lines fear with its regiron and sulfurssing through tn this case, bott clear that therrising because

hat satisfactoryshows that the

atter Deposition Interpretati

weight percentfor the two eleression line (Rr were in the fthe origin, as sth trend lines thre is an excessiron occurs in

y calibrations cere is an excess

and Preservatiion Ltd, Bidefor

tages from corements have d

R2=0.55), whileform of pyritehown in the rihrough the irons of iron beyonminerals other

cannot be obtais of sulfur (i.e.,

on. Courtesy: Crd, UK.

re versus LECOdifferent slopese the iron poine, and pyrite coight-hand panen points have and what wouldr than pyrite; iined to predict, not all of the

C Cornford, Inte

O TOC for Wes and non-zeronts are more disorrelated perfeel, and the ratioa steeper slope d combine within this examplet TOC from susulfur is assoc

egrated Geoche

ell 1. The left-o y-intercepts. spersed about ectly with TOCo of the iron s than regressio

h available sulfe, most of the iulfur and/or pyiated with pyri

5

mical

hand panel The sulfur the best-fit C, the data slope to the ons through fur to form iron occurs yrite in this ite).

6

powqth

6

Fig. 5—Iron

From the copyrite in Well of the iron poinweight percentquantities sugghe XRD analy

Fig. 6—Pyrite

Sulfur - TOC (W

ore elemental r1, which meannts in Fig. 5 artages from IC

gests that most sis that most o

vs. Sulfur CoreSu

Well 1). The left

results shown ns that the majore not well corrCP measureme

of the iron in f the iron occu

e Results Showulfur.

plot displays gethro

in Fig. 7, thereority of iron isrelated with TOents performedthis well is ass

urs in illite clay

ing an Excess o

eneral regressiough the origin.

e is far greaters present in anoOC. Fig. 8 shod on Well 1 sociated with ay.

of Fig. 7

on lines, and th

r iron present tother mineral fows a cross-plocores. The w

alumino-silicat

7—Iron and Sulf

he right plot forc

than needed to form, and it exot of iron oxide

well-defined cote minerals. In

fur Core Results

S

ces the regress

bind with sulfxplains why the versus alumiorrelation betwthis case, we k

s for Haynesvill

SPE 161097

ion line

fur to form he grouping inum oxide ween these know from

e Well 1.

S

PAfm

cc

ocw

rp

thv

SPE 161097

Pyrite-TOC RA total of 588 from Well 1 measurements w

Fig. 9 showcore measuremcoefficient. Wh

All of the aorigin, reflectincorrelations betwell-by-well ba

For some wrecognized. It iperhaps becaus

An interestihe Haynesville

varying anoxic

Relationship core samples fincludes a fulwere performe

ws a compositements. The reghen data from i

Fig. 9—

available data fng the assumptween pyrite anasis. wells, outliers is believed thase of a loss of Ting observatione play, while w conditions tha

from the Haynll suite of lab

ed on the core se cross-plot of gression line hindividual well

—Composite Cro

for each well isption that all ond TOC that ca

(surrounded at these points TOC recovery. n is that the TOwells closer toat would affec

Fig. 8—Hayn

nesville shale wboratory meassamples. XRD pyrite ve

highlights a linls are examined

oss-plot of Core

s shown in Figof the pyrite isan be used to c

with red squaare biased tow

OC-Pyrite (y = the center of t the amount o

esville Well-1 IC

were available surements. For

ersus LECO Tnear trend amd, a more enco

Data from Nine

. 10. Regressios associated wicalibrate a TOC

ares) from theward the upper

= Pyrite, x = TOthe play have

of pyrite forme

CP Data.

from the niner the remainin

OC for all ninmong the data,

uraging picture

e Haynesville W

on lines are shoith TOC. ViewC indicator usin

e trend througr left because o

OC) slopes arelower slopes.

ed. If true, it im

e wells selectedng eight well

ne wells. The d, but with a de emerges, as s

Wells in 8 counti

own for each wwed this way, ng a log-derive

gh the majorityof the way the

e largest for we These variatiomplies sulfur a

d for this studys, only XRD

data includes aldisappointing shown in Fig. 1

es.

well that pass tit is easier to

ed pyrite asses

y of the data e sample was s

ells on the outeons may be inand pyrite TOC

7

y. The data and TOC

ll available correlation 10.

through the o see linear ssment on a

are easily selected, or

er fringe of ndicative of C indicator

8

cg

IPpefoti7

iSpTlo CWc

8

calibrations mageographical ar

nfluence of PPyrite has a veporosities becaevery 1% volumfor the first 10%of pyrite is sligimes. Clavier e

7% pyrite by voIt is import

s used. The deSimilarly, the pyrite mask theTOC indicator ogs.

Comparison Wireline elemecomposition of

ay need to be rea.

Pyrite on Logery high densi

ause of its impme of pyrite in% of pyrite at aghtly less thanet al. (1976) coolume; the addant to considerensity-resistivitsonic-resistivite influence of will be negligi

of Laboratorental logs provf reservoir rock

localized, as

Fig. 1

gs ity (5 g/cm3), act on grain dn the rock. Fora rate between n calcite and doncluded that t

dition of pyrite r these influenty DeltaLogR ty DeltaLogR organic matterible because py

ry ICP and Wvide concentrak. A volumetri

it appears for

0—Haynesville

and its presendensity. It causr thermal neutr0.3 and 0.4 po

dolomite, whichthe resistivity rin the formatio

nces on log-derTOC indicatorTOC estimate

r. On the otheryrite affects bo

Wireline Elemations of specc breakdown o

the Haynesvi

Pyrite XRD ver

nce increases bes a reductionron tools, pyrit

orosity % per 1h means its prreadings will bon lowers the orived TOC indir will also tende will be slighr hand, the infloth logs in a w

mentals cific elements,of mineralogy

ille shale, rath

rsus LECO TOC

bulk density, wn in calculated te causes a nea% pyrite (Hilcresence will tebe in severe erobserved resist

dicators, especid to be somewhtly pessimistiluence of pyrit

way that does no

which are hecan be obtaine

er than genera

C.

which leads todensity porosiarly linear incr

chie 1982). Theend to shorten rror in formatiotivity because iially when Paswhat pessimistic because the te on the neutrot mask the dif

elpful in idented by apportion

S

ally applied ov

o pessimistic dity of 1.4 pororease in neutroe compressionaobserved acou

ons containingit is highly consey’s DeltaLogic with increascombined inf

ron-resistivity Dfference betwe

tifying the minning measured

SPE 161097

ver a large

density-log osity % for on porosity al slowness ustic travel more than

nductive. gR method sing pyrite. fluences of DeltaLogR een the two

neralogical d elemental

S

cmdb

ceoscmlav

LToTswmc1mTm

SPE 161097

concentrations momentum widetected, etc. Tby providing di

To be useconcentrations.elemental concoxides SiO2, Csolid black circcurve in track method comparaboratory-mea

volume of form

Log-derived STOC core measof the density-TOC values. Trslope and offsewhich was obtamulti-mineral lcurve shown in10, Well 1. Depmedian averageThe results, formiddle of the in

according to mith improveme

The geochemicairect measuremeful for mine Fig. 11 show

centrations derCaO, Al2O3, K2

cles, and red c8 shows TOC

red with LECOasured elementmation material

Fig. 11—Wire

Sulfur and Pyrsurements from-resistivity, nerack 2 shows aet from the corained by makinlog analysis son track 3 by usipicted in track e TOC estimatr the most partnterval are bett

Fig. 12—

mineral chemients in equipmal logging serv

ment of 10 elemeral identificas elemental corived from lab2O, Fe2O3, andcurves show wC derived fromO TOC measutal concentratiol compared to t

eline and Labora

rite TOC Resm Well 1 in theutron-resistivit

an overlay of Trrelation of sung an initial paolver. The FAMing regression 4 is an overlaye obtained by at, are not radicater represented

—Log-derived T

istry. Elementament design, mvice offers a rapments (Si, Ca, Aation, log-meancentrations ob

boratory measud TiO2) and ED

wireline concenm neutron, denurements perforons is quite gthe samples use

atory Elemental

ults. Displayee study. The blty, and sonic-r

TOC calculatedlfur versus TO

ass through HaME dry-rock pparameters fro

y of the medianapplying the mally different f

d by the median

TOC wt% Value

al logging has materials, elecpid and preciseAl, Fe, K, S, Tiasured elemenbtained with thurements perfD-XRF (S). In

ntrations, whernsity, sonic, anrmed on core sood when it ied to carry out

l Concentration

d in Fig. 12 arlack curve in trresistivity Del

d from the GEMOC in Fig. 5. Palliburton’s Flupyrite wt% outpom core-measun average of th

median averagefrom the DeltaLn average of all

s from DeltaLog

been in existectronics, gamme evaluation ofi, Gd, Mn, andntal concentrahe GEM tool iformed on corn tracks 1–7, cre the oxide-oxnd resistivity samples. In geis recognized tt the laboratory

s from Well 1 o

re log-derived rack 1 is a medltaLogR indicaM™ tool’s geoPresented in truids and Minertput curve wasured pyrite andhe DeltaLogR ie to the DeltaLLogR-only avel five indicator

gR, Sulfur, and

ence for over ma-ray detectof formations wid Gd) (Galford ations must rin the Haynesvre material usicore-derived rexygen has beenlogs by apply

eneral, the agrethat logs samp

y measurement

f the Haynesvil

TOC indicatodian average (Hators; red circ

ochemical sulfurack 3 is TOC rals Evaluations then used to d TOC, slope, aindicators (samogR, sulfur, anerage; a few ors.

Pyrite Indicator

40 years and ors, number oith complex met al. 2009).

reflect actual ville shale coming ICP-OES esults are reprn removed. Th

ying Passey’s Deement betweeple a substantits.

le Study.

ors compared wHodges-Lehmacles show coreur measuremen

from log-derin (FAME)™ prcalculate the Tand y-intercep

me curve as tracnd pyrite TOC f the core poin

rs.

9

has gained f elements

mineralogies

formation mpared with

(measured resented by he magenta DeltaLogR en log- and ially larger

with LECO an average) e-measured nt using the ved pyrite, robabilistic TOC pyrite t from Fig. ck 1) and a indicators.

nts near the

1

IuclaT

Ft2

1dthl

0

Interpretationunaccounted-focontemporaneoess than approx

adjustment for TOC. This is hy

Fig. 13—Relatioheroretical limi

2010).

Using the P14. The red arrdensity of apprhan 5%; the gress than 5 wt%

n Example: Haor pyrite decreaous effect is illuximately 4–5 wTOC is adequaypothesized to

n between TOCts for siderite-r

Passey’s cross-prow demonstraroximately 2.7rain density ap

%, with a maxim

aynesville Welasing the predicustrated by Figwt%, an interprate. For values be a result of o

C and dry grain rich and illite-r

plot template fates that for TO1 g/cc with an

ppears to have mum TOC of 8

ll. As previouscted porosity a

g. 13 below, froretation assumiof TOC greate

other mineral,

density for samrich mudstones

for Well 1, the OC less than apn adjustment foa correlation w

8.21 wt%.

ly mentioned, and unaccounteom Passey et aing a constant er than 5%, thesuch as calcite

mples from an ils, assuming the

contemporanepproximately 4or TOC is adewith TOC. For

pyrite and TOed-for TOC incal. 2010. The re

grain density oe grain density e and dolomite

lite clay-rich ore kerogen grain

ous effect of p4–5 wt%, an inequate. The TOr the nine wells

C appear contecreasing the pred arrow demoof approximateappears to hav, plus perhaps

rganic-rich mudn density is 1.1

pyrite and TOCnterpretation aOC values for s, 98.5% of the

S

emporaneouslyedicted porositnstrates that fo

ely 2.8 g/cc witve no correlatiopyrite.

dstone. Also sho1 g/cc (from Pa

C is also illustraassuming a con

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Fig. 14—Haynesmudstone. Also1.1 g/cc. Actual

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much of the C and, to a

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Fig. 16—Comparison of Method 2 (Blue) and Method 3 (Red) Results with Core Data.

Summary and Conclusions Core results from nine Haynesville shale wells in eight different counties of East Texas and northwest Louisiana show correlations between pyrite and TOC. From this data, it is clear that the slope of the relationship between pyrite and TOC varies from well to well and generally increases toward the periphery of the play and may be linked to depositional conditions.

The correlation functions in Fig. 10 were forced through a zero intercept, assuming that all pyrite is associated with TOC. Somewhat better correlation coefficients, R2, can be observed by regressing for both slope and non-zero intercept, which may suggest that small amounts of detrital pyrite also exist or that there is a systematic bias in the XRD results.

As expected for the anoxic depositional environment, a good correlation between sulfur and TOC is observed for the Haynesville shale.

As demonstrated, properly calibrated TOC indicators from log-derived sulfur and pyrite can be combined with other log-derived indicators to improve the overall estimate of TOC in the Haynesville shale and other shale plays.

For much of the well with complete log and core data, much of the variation of grain density resulted from an increase of TOC so that an adequate interpretation could be made using just TOC obtained from the averaging of several indicators along with the assumption of constant matrix (excluding TOC) grain density.

Using all log data, such as neutron and density logs, geochemical logs, and shallow- and deep-resistivity logs, as well as TOC, add to the reliability of the interpretation. Only this approach agreed adequately with core data, where the grain density was rapidly varying through the Haynesville formation and carbonate section. Acknowledgement The authors would like to acknowledge BP America for an earlier release of the geochemical log data, core analyses, and bulk-rock elemental data used in this and previous studies. The BP America data pertains to one well used in this study. We also would like to thank those who also contributed data for this paper. References Clavier, C., Heim., A., and Scala. C. 1976. Effect of pyrite on resistivity and other logging measurements. Paper HH presented at the 17th

Annual Logging Symposium Transactions: Society of Professional Well Log Analysts, p. HH1–34. Cornford, C. 2004. The Petroleum Systems, 268-294. Oxford: Elsevier. Eastler, Dr. 2006. Black Shales PowerPoint, Brian Way, Sedimentary & Stratigraphy, December 1, 2006. Galford, J., Truax, J., Hrametz, A., and Haramboure, C. 2009. A new neutron-induced gamma-ray spectrometry tool for geochemical

logging. Paper X presented at the 50th Annual SPWLA Logging Symposium, Houston, Texas, USA, 21–24 June. Hammes, U. Depositional Environment, Sequence Stratigraphy, and Petrophysical and Reservoir Characteristics of the Haynesville and

Bossier Shale-Gas Plays of East Texas and Northwest Louisiana. Bureau of Economic Geology, The University of Texas at Austin, www.beg.utexas.eduu/abs/Hammes_2011-05-06.php. Downloaded 1 May 2012.

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Hammes, U., Hamlin, H., and Ewing, Thomas E. 2011. Geologic Analysis of the Upper Jurassic Haynesville Shale in East Texas and West Louisiana. AAPG Bulletin 95 (10): 1643–1666.

Hilchie, D.W. 1982. Advanced well log interpretation. Golden, Colorado: Douglas W. Hilchie, Inc. Klimentos, T. 1995. Pyrite Volume Estimation by Well Log Analysis and Petrophysical Studies. The Log Analyst 36 (6): 11–17. Inductively Coupled Plasma Spectroscopy (ICP-OES/MS). Evans Analytical Group, http://www.eaglabs.com/mc/inductivity-coupled-

plasma-spectorscopy.html. Downloaded 1 June 2012. McGraw-Hill Encyclopedia of Science and Technology, 5th edition, published by The McGraw-Hill Companies, Inc. Passey, Q.R., Creaney, S., Kulla, J.B., Moretti, F.J., and Stroud, J.D. 1990. A practical model for organic richness from porosity and

resistivity logs. AAPG Bulletin 74 (12): 1777–1794. Passey, Q.R., Bohacs K.M., Esch W.L., Klimentidis R., and Sinha S. 2010. From Oil-Prone Source Rock to Gas Producing Shale Reservoir

- Geologic and Petrophysical Characterization of Unconventional Shale-Gas Reservoirs. Paper SPE 131350 presented at the CPS/SPE International Oil and Gas Conference and Exhibition, Bejing, China, 8–10 June.

Pope, C., Peters, B., Belton, T., and Palish, T. 2009. Haynesville Shale – One Operator’s Approach to Well Completions in this Evolving Play. Paper SPE 125079 presented at the Annual Technical Conference and Exhibition, SPE, New Orleans, Louisiana, USA, 4–7 October.

Quirein, J., Galford, J. Witkowsky, J., Buller, D., and Truax, J. 2012. Review and Comparison of Three Different Gas Shale Interpretation Approaches. Paper SPWLA-D-11-00075 presented at the SPWLA 53rd Annual Logging Symposium, Cartagena, Colombia, 16–20 June.

Quirein, J., Witkowsky, J., Truax, J., Galford, J., Spain, D., and Odumosu, T. 2010. Integrating core data and wireline geochemical data for formation evaluation and characterization of shale gas reservoirs. Paper SPE 134559 presented at the SPE Annual Technical Conference and Exhibition held in Florence, Italy, 19–22 September.

Ruessink, B.H. and Harville, B.V. 1992. Quantitative Analysis of Bulk Mineralogy: The Applicability and Performance of XRD and FTIR. Presented at the SPE Formation Damage Control Symposium, Lafayette, Louisiana, USA, 26–27 February.